pyemfield 0.1.6

A Python library for HFSS antenna radiation pattern analysis and gain optimization

pyemfield: Python Antenna Radiation Analysis and Optimization Library

pyemfield is a Python library designed for antenna radiation pattern analysis and gain optimization. The package leverages SciPy, NumPy, Matplotlib, and ANSYS HFSS (via pyaedt) to automate high-frequency structure simulations, process electromagnetic data, and visualize results.

Key Features

• Gain Calculation and Optimization: Provides methods to calculate antenna gain with multiple optimization options, including exhaustive, heuristic, and SciPy-based optimizations.
• Radiated Power Density and Cumulative Distribution: Calculates and visualizes cumulative distribution functions (CDFs) for radiation characteristics.
• Custom Radiation Pattern and Gain Distribution Plots: Offers multiple plotting functions to visualize radiated power density, gain, and other related data.
• Integration with HFSS: Automates the export of far-field data from HFSS simulations for further analysis and optimization.

Installation

You can install the package using pip:

pip install pyemfield

Note: Ensure that pyaedt and ANSYS HFSS are installed to fully utilize all functionalities in this package.

Dependencies

This package requires the following libraries:

• numpy
• scipy
• matplotlib
• pyaedt

Quick Start

1. Basic Usage Example

The following example demonstrates how to use pyemfield to calculate and visualize antenna gain:

from pyemfield import hfss_design, get_ffds, Beam

folder = r'D:\OneDrive - ANSYS, Inc\GitHub\pyemfield\tests\ffds'
ffds = get_ffds(folder)

ffds.keys()

x = {j:(1,0) for i, j in ffds.items()}
b1 = Beam(x)

b1.ffd_excitation
b2 = b1.optimize_gain(60, 60)
b2.plot_realized_gain_contour()
b2.ffd_excitation

hd.update_excitation(b2.ffd_excitation)

2. Create a Custom Plane and Plot Cumulative Distribution

# Set up multiple beams and create a Plane
plane = create_plane("MyPlane", beam, [(0, 0), (90, 90)], fast=True)
plane.plot_rGain_cdf()
plane.plot_eirp_cdf()